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1. 1. PREDICTION OF WIND TURBINE BLADE FATIGUE LOADS USING FEED-FORWARD NEURAL NETWORKS

   Master-uppsats, Uppsala universitet/Institutionen för geovetenskaper

   Författare :Mohammad Mehdi Mohammadi; [2021]
   Nyckelord :Machine Learning; Feed-Forward Artificial Neural Network; Wind Power; Damage Equivalent Loads; Fatigue; Wind Turbine Blades; NEWA Data; SCADA; Lillgrund Wind Farm;

   Sammanfattning : In recent years, machine learning applications have gained great attention in the wind power industry. Among these, artificial neural networks have been utilized to predict the fatigue loads of wind turbine components such as rotor blades. LÄS MER